System and Methods for Converting Speech to SQL

TL;DR

This paper presents a system that converts spoken English queries into SQL commands using acoustic models, language processing, and rule-based translation techniques, enabling natural language database querying.

Contribution

It introduces a domain-independent framework combining speech recognition and rule-based translation to convert spoken queries into SQL, adaptable to different databases.

Findings

Achieved conversion of spoken queries to SQL with high accuracy

System supports multiple database domains without retraining

Utilizes existing tools like HTK, Julius, JFLex, and BYACC

Abstract

This paper concerns with the conversion of a Spoken English Language Query into SQL for retrieving data from RDBMS. A User submits a query as speech signal through the user interface and gets the result of the query in the text format. We have developed the acoustic and language models using which a speech utterance can be converted into English text query and thus natural language processing techniques can be applied on this English text query to generate an equivalent SQL query. For conversion of speech into English text HTK and Julius tools have been used and for conversion of English text query into SQL query we have implemented a System which uses rule based translation to translate English Language Query into SQL Query. The translation uses lexical analyzer, parser and syntax directed translation techniques like in compilers. JFLex and BYACC tools have been used to build lexical analyzer and parser respectively. System is domain independent i.e. system can run on different database as it generates lex files from the underlying database.